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Workshop Mon, Dec 14, 2026 • 12:00 AM – 9:00 AM AEDT C111-112

Second Workshop on MLxOR: Mathematical Foundations and Operational Integration of Machine Learning for Uncertainty-Aware Decision-Making

Minshuo Chen ⋅ Jing Dong ⋅ Henry Lam ⋅ Karthyek Murthy ⋅ Min-hwan Oh ⋅ Devavrat Shah ⋅ Renyuan Xu ⋅ Enlu Zhou

Project Page [ OpenReview]

Abstract

This workshop aims to present recent developments, discuss challenges, and publicize emerging research opportunities in data-centric decision-making that leverage both the rapid advancement of ML and the principled methodological rigor of OR. Through tools ranging from stochastics to optimization, OR is capable of translating explicit modeling assumptions into interpretable and risk-quantifiable solutions, making it central to reliable decision-making across a wide range of industry applications. At the same time, the analytical tractability of OR models also restricts the level of real-world complexity that they can tackle. To this end, rapid advances in AI/ML offer a powerful opportunity to complement traditional OR and substantially improve decision performance, while, conversely, decades of rigorous OR research can help address key challenges surrounding black-box systems in AI/ML. Building on the momentum of the inaugural workshop in 2025, this second launch of the workshop will continue to explore this two-way OR-ML synergy, this year with a focus in "GenAI", which broadly refers to generative models, including language models, diffusion models, and related foundation models, that can represent, generate, and reason over complex, multimodal scenarios and actions. The emergence of GenAI has already begun to reshape research in OR and shown promise in producing decisions at a scale and complexity previously unattainable, yet it also raises fundamental challenges around evaluation, reliability and safety that counteract the core principles of OR. This theme is thus urgent and impactful in steering the future OR direction. The goal is to bring together researchers from diverse backgrounds to develop a shared understanding of the emerging challenges and opportunities at the GenAI-OR interface, ultimately laying rigorous foundations for reliable, uncertainty-aware, and resource-efficient decision-making.

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Schedule

Time zone: Conference local time zone

Sharp Characterization of Bias in Post-Bandit Inference

Lisu Wang ⋅ Yilun Chen ⋅ Jiaqi Lu

Value-Filtered Expert Query for Efficient Language Agent Finetuning: an Empirical Study

Junze Ye ⋅ Miao Lu ⋅ Jose Blanchet ⋅ Mohsen Bayati

Exact Predictions Do Not Determine Continuous Margins in Differentiable Decision Trees

Pedro Chumpitaz-Flores ⋅ My Duong

Validation-Selected Post-Hoc Calibration of Joint Crash Risk in Multi-Asset Scenario Generators

Yanhui Ren ⋅ Ximan Sun

The Risks and Rewards of User Expressiveness in Revenue-Driven Recommendation

Rigel Galgana ⋅ Yeganeh Alimohammadi ⋅ Negin Golrezaei

Neural Scaling Laws for Customer Choice Prediction

Ozan Candogan ⋅ Ayoub Foussoul ⋅ Feiyu Han

OPTAgent: From Standalone Solvers to Deployment-Aware Solver Ecosystems

Hanyang Jiang ⋅ Changkun Guan ⋅ Miao Li ⋅ Danlin Li ⋅ Sikai Cheng ⋅ Pascal Van Hentenryck ⋅ Russell Bent

The Critic Is Only a Proxy: Regret Optimization for Reinforcement Learning

Yikai Wang ⋅ Shang Liu ⋅ Guanting Chen ⋅ Jose Blanchet

A Model-Agnostic Laplacian Criterion for Assortment Experiment Design

Xintong Yu ⋅ Will Ma

Artificial Intelligence Clones and Matching Markets

Akshit Kumar ⋅ Vahideh Manshadi

ASTOR: Benchmarking and Improving Autoformulation for Soft-Constraint Optimization with a Formal Grammar

Amer Goel ⋅ Yeganeh Alimohammadi ⋅ Andrew Daw

Loss-Aware Selection of Dependence Information in Distributionally Robust Optimization

Yu Ma ⋅ Peilin Yang

Decision-Aware Utility Learning for Assortment Optimization

Hansheng Jiang ⋅ Sheng Liu ⋅ Daniel Zhuoyu Long ⋅ Yu Sun ⋅ Ruxian Wang

Active Ranking via Minimizing the Sum of Top-$k$ Regrets

Motti Goldberger ⋅ Nils Rudi

How Much Distribution Shift Changes a Conclusion?

Jonathan Zhou ⋅ Rohan Kumar

Differentiating Through Dual Prices: End-to-End Policy Learning Under Capacity Constraints

Mohammadsaeed Haghi ⋅ Nima Kelidari ⋅ Salmani ⋅ Vishal Gupta ⋅ Phebe Vayanos

BATCHPACE - Global Budget LLM Routing under Batched Arrivals

HeoSeojun ⋅ Doyoung Heo

When Should I Pay for Better LLMs? Stochastic Optimization with Switching Mixed-Fidelity Oracles

Swati Gupta ⋅ Tianjiao Li

Geometry-Informed Tracing of Model Adaptation Path under Protected-Capability Constraints

Hao Hao ⋅ Peter Zhang

Learning Risk-Averse Policies with Two-Stage Deep Decision Rules

Olivier Demers ⋅ Maryam Daryalal ⋅ Michel Denault

Learning to Communicate Under Alignment Uncertainty: Bayesian Persuasion Bandits

Wenqian Xing ⋅ Ramesh Johari

Population-Aware Primal--Dual Coordination for Large-Scale Multi-Agent Systems

Angel Wang ⋅ Dominique Perrault-Joncas ⋅ Alvaro Maggiar ⋅ Dean Foster ⋅ Carson Eisenach

JAREX: An Acquisition Function for Multi-Objective Algorithmic Process Characterization

Xinyang Li ⋅ Kevin Stone ⋅ Ajit Vikram

AI Agents for Inventory Control: Human-LLM-OR Complementarity

Jackie Baek ⋅ Yaopeng Fu ⋅ Will Ma ⋅ Tianyi Peng

A Geometric Approach to Constrained Online Learning

Dhruv Sarkar ⋅ Abhishek Sinha

Model-Robust and Sequentially Valid Moment Certificates for Chance-Constrained Stopping

Doyoung Heo ⋅ Donggyu Kim ⋅ SooJean Han

LLMs Make Robust Stochastic Optimization Easier: An Agentic Workflow

Ziyu Wang ⋅ Zhuolin Wang ⋅ Yi Chen ⋅ Zhi Chen ⋅ Guodong Lyu

Decision-Aware Generative Demand Learning for Contextual Newsvendor Optimization via Quantile Sensitivities

Zhou Miao ⋅ Zhiyuan Huang ⋅ Zhaolin Hu ⋅ Hongyi Jiang

Automating MIP Solver Configuration with Large Language Models

Michael Zhang ⋅ Justin Okamoto ⋅ Antonia Chmiela ⋅ Oleksandr Radomskyi ⋅ Christian Schulz ⋅ Jeremy L Wyatt

Decision-Improved Predictions

Mengchu Yue ⋅ Connor Lawless ⋅ Angela Zhou

QueueAgentBench: An Experimental Testbed for AI-Agent Queueing Formulation from Event Traces

Yunduan Lin ⋅ Weiliang Liu ⋅ YIFAN LI ⋅ Haoting Zhang

Real-World Adaptation and Enhancement of Recurrent Marginal Structural Networks to Estimate Causal Impact of Sales and Account Management Teams

Zhiyuan Shen ⋅ Shuo Yang ⋅ Ashish Patira ⋅ Hossein Keshavarz ⋅ Michelle Song ⋅ Saad Zaheer ⋅ Palash Siddamsettiwar ⋅ Joey Kao ⋅ Xiaoyi Cheng ⋅ Emmanuel Ekwedike ⋅ Matthew Sisco ⋅ Lei Kang ⋅ Khalifeh AlJadda

Toward High-Fidelity LLM Simulation: Lessons from a Mobilization Experiment

Mohamad Sadegh Shirani Faradonbeh ⋅ William Overman ⋅ Mohsen Bayati

Low Dimensional Sampling under Reconstructed Constraints

Imon Banerjee ⋅ Riddhiman Bhattacharya

Causal Reward Alignment for Counterfactual Scenario Generation

Matea Gjika ⋅ Giuseppe Iannone ⋅ Luca Sfragara ⋅ Pavithra Harsha ⋅ Georgia Perakis

Incentivizing Exploration with Returning Agents: Bandits for Invasive Species Removal

Icey Ai ⋅ Lily Xu

OR-Transformer: Scaling Real-Time Decision-Making to 1,000 Items

Shuze D Liu ⋅ David Simchi-Levi ⋅ Claire Chen ⋅ Chutong Gao ⋅ Shangtong Zhang

Integrating Large Language Models with Optimization for Interactive Power Systems Planning

Sergio Bugosen ⋅ Tomas Valencia Zuluaga ⋅ Jean-Paul Watson ⋅ Chrysanthos E Gounaris ⋅ Carl Laird

Visual Polarization Measurement Using Counterfactual Image Generation

Mohammad Mosaffa ⋅ Omid Rafieian ⋅ Hema Yoganarasimhan

Trajectory-Adaptive Stopping Rules for SGD under Strong Convexity

Liviu Aolaritei ⋅ Lucas Lévy ⋅ Francis Bach ⋅ Michael Jordan

Anytime-Valid Federated Conformal RAG for LLM Swarms

Prasanjit Dubey ⋅ Xiaoming Huo

When Similar Models Disagree: Validation-Induced Decision Instability in Clinical Trial Portfolio Selection

Michael Doane

Multi-Turn LLM Conversations under the Least-Recently-Used Policy: Mean-Field Asymptotics and Hit Ratio Approximation

Heyuan Yao ⋅ Chutong Gao ⋅ Yuan Lyu ⋅ Isaac Grosof ⋅ David Simchi-Levi

Efficient Clustering of Transformer-Induced Slate Spaces

Lin An ⋅ Ben Moseley ⋅ Helia Niaparast

Scalable Robust-Policy Learning under Total-Variation Uncertainty

Saptarshi Mandal ⋅ Yashaswini Murthy ⋅ R. Srikant

Deciding Pipeline Order Under Joint Severity Shift: From Local Diagnostics to Target-Law Performance

Jiahang (Hank) Sha ⋅ Wei Wang

ViAR: A Visual Autoregressive Router for the Capacitated Vehicle Routing Problem

Asma CHERRERED ⋅ Ammar OULAMARA ⋅ Wahiba R Cherif-Khettaf

Distilling Tabular Foundation Models to Simple Decision Trees

Hayden McTavish ⋅ Daniel Kerrigan ⋅ Brian Barr ⋅ Samuel Sharpe ⋅ Nam Nguyen

Biobjective Pareto Solution Mapping with Application in Group Lasso Regularization Path

Guanting Wu ⋅ Peter Zhang

Registration Is Not Enough: Online Relation Recommendation over Growing Schema Registries

Mintaek Oh

A Continuous-Time Reinforcement Learning Framework for Fine-Tuning Discrete Diffusion Models

Zikun Zhang ⋅ Jiayuan Sheng ⋅ David Yao ⋅ Wenpin Tang

A Joint CLT for UCB-Generated Data

Yilun Chen ⋅ Jiaqi Lu

Directionally Correct Views in Portfolio Optimization

Ojas Kumar ⋅ Sreejit Dey ⋅ Sarvesh R Iyer ⋅ Sandeep Juneja

Bridging Predictive ML and Prescriptive Operations Research: Resource Allocation via Mamba-Based Model Prediction Control

Oded Schlesinger ⋅ Vivek Singh ⋅ Nikhil Shenoy ⋅ Klaus Kirchberg ⋅ Ankur Kapoor ⋅ Dorin Comaniciu ⋅ Guillermo Sapiro

Fictitious Play When Agents Are Not Expected-Utility Maximizers: A Geometric Analysis in $2$-Action Games

Hao Liang ⋅ Solaleh Mohammadi ⋅ Kaiqing Zhang

Preventing Model Extraction in Contextual Linear Optimization

Adam N. Elmachtoub ⋅ Tianyi Lin ⋅ Wenxuan Liu

Eviction as a Scheduling Decision in LLM Inference

Xinyu Liu ⋅ Zheng Guo

Recommendations as Designed Experiments: Active Inverse Optimization for Identifiable Preference Learning under Hard Constraints

Farzin Ahmadi ⋅ Kimia Ghobadi

Sparse Mean-Variance Portfolio Selection under Ellipsoidal Uncertainty

Deniz Akkaya ⋅ Emre Can Yayla ⋅ Buse Şen ⋅ Mustafa C PINAR

Adapting to Evolving Requirements: Agentic AI for Retail Supply Chain Operations

Lei Zheng ⋅ Liping Yang ⋅ Zihao Li ⋅ Guodong Lyu ⋅ Chung-Piaw Teo ⋅ Chaik Ming Koh

AI vs. Human Search

Ming Hu ⋅ Hansheng Jiang ⋅ Sheng Liu ⋅ Yu Sun

Source-Aware Uncertainty Quantification for Decision-Making with Large Language Models

Hiba Cheikh ⋅ Sara El Mekkaoui ⋅ Loubna Benabbou

COSMOS: Dynamic Latent-State Discovery under Multivariate Drivers

Matea Gjika ⋅ Georgia Perakis

Learning to Parameterize Recourse Models for Large-Scale Stochastic Optimization

André H Paredes ⋅ Tomas Valencia Zuluaga ⋅ Jean-Paul Watson ⋅ Gonzalo Constante

RELAGRAM: Recursive Latent Graph Model for Capacitated Vehicle Routing Problem

Vladimir K Bickov ⋅ Neil Yorke-Smith

Spec2Twin-Chain: Building Blockchain Digital Twins with LLM-Guided Bi-Level Optimization

Haoting Zhang ⋅ Jiayuan Sheng ⋅ Haoxian Chen ⋅ Donglin Zhan ⋅ Zeyu Zheng ⋅ David Yao ⋅ Wenpin Tang

Generate-and-Select: A Simple Framework for Bayesian Optimization with LLM Proposals

Shorya Sharma ⋅ Peter Frazier ⋅ Raul Astudillo

Duality and Policy Evaluation in Distributionally Robust Bayesian Diffusion Control

Jose Blanchet ⋅ Jiayi Cheng ⋅ Yuewei Ling ⋅ Hao Liu ⋅ Yang Liu

What Should Predict-then-Optimize Predict? Feature Design from a Scaffold Distribution

Alice Duan ⋅ X.Y. Han ⋅ Feng Ruan

Nested Convex-Body Chasing for Online Optimization with Evolving Feasible Sets

Dhruv Sarkar ⋅ Aprameyo Chakrabartty

Multistage Power Grid Capacity Expansion Planning under Uncertain AI Data Center Demands

Chengyi Cai ⋅ Wei Gu ⋅ Shixiang Zhu ⋅ Peter Zhang

Calibrating Mechanisms with Delayed Evidence

Yuchen Hu ⋅ Stephen Bates ⋅ Martin Wainwright

What Would it Cost to End Extreme Poverty?

Roshni Sahoo ⋅ Joshua Blumenstock ⋅ Paul Niehaus ⋅ Leo M Selker ⋅ Stefan Wager

A Transformer-Based Choice Model for Multiple Choice with Context and Basket Effects

Salvador K. Dzimah ⋅ Manuel Moran-Pelaez ⋅ Georgia Perakis

Risk-Aware Best-of-$N$

Yichun Hu ⋅ Meng Qi

LLM-SAA: LLM-persona Generated Distributions for Decision-making

Jackie Baek ⋅ Yunhan Chen ⋅ Ziyu Chi ⋅ Will Ma

AI-Generated Measurements for Identification and Inference with Missing Data: A Weak Shadow Variable Approach

Hongyu Chen ⋅ David Simchi-Levi ⋅ Ruoxuan Xiong

Fluid Value Functions for Policy-Gradient Algorithms

Itai Gurvich ⋅ Céline Comte

Candidate Completion: Exact Off-Policy Calibration of Implicit Best-of-$M$ Sequential Policies

Aditya S Patil

MARCS: Marginal-Cost Routing and Adaptive Priority Control for LLM Inference

Yuan Cao ⋅ Ruicheng Ao ⋅ Will Ma ⋅ David Simchi-Levi

Off-Context GRPO: Learning to Reason on Hard Problems using Privileged Information

Priyank Agrawal ⋅ Ankur Samanta ⋅ Shervin Ghasemlou ⋅ Boris Vidolov ⋅ Jalaj Bhandari ⋅ Kavosh Asadi ⋅ Daniel Jiang ⋅ Aditya Modi

Solver-Free Decision-Focused Learning via Barrier Coordinate Cost Prediction

Jonathan Hornewall ⋅ Vincent Leclere

Verifier-Native Closed-Loop Repair for Operations Research Agents

Ruicheng Ao ⋅ Chenyang Ma ⋅ David Simchi-Levi ⋅ Wang

Meaning-Preserving Rephrasings Can Break LLM-Generated Optimization Models

Jessica Udomsrirungruang ⋅ Anirudh Subramanyam

Satisficing Regret Minimization under Nonstationarity

Yixuan Zhang ⋅ Ruihao Zhu ⋅ Qiaomin Xie

Flexible but Fragile: Budgeted Human--Digital-Twin Allocation for A/B Tests

Iris Ye ⋅ tianze deng ⋅ Ozan Candogan

What You Say Versus When You Say It: Efficiently Predicting Service Completions with LLMs and Stochastic Processes

Antonio Castellanos ⋅ Andrew Daw

Locally Minimax Pseudo-Variance Adaptive Contextual Bandits for Heavy-Tailed Pareto Payoffs

Sungchan Ahn ⋅ Wonyoung Kim

Logarithmic Regret for Single-Sample Nonstationary Online Linear Programming

Dhruv Sarkar ⋅ Aprameyo Chakrabartty

Proximal Residual Value Functions for Consistent Real-Time Inventory Placement

Harrison Waldon ⋅ Carson Eisenach ⋅ Akhil Bagaria ⋅ Daniel Russo ⋅ Dominique Perrault-Joncas ⋅ Alisha Zachariah ⋅ Dean Foster

Large Language Models for Sequential Decision-Making: Improving In-Context Learning via Supervised Fine-Tuning

Minmin Zhang ⋅ Sina Aghaei ⋅ Soroush Saghafian

Report Resolution in Federated Multiple Testing: An Inverse-Square Law for Power Loss

Prasanjit Dubey ⋅ Xiaoming Huo

Very High-Dimensional Slope Change Detection with Guarantees

Apoorva Narula ⋅ Santanu Dey ⋅ Yao Xie

From Mobility Trajectories to EV Charging Decisions: Recovering Latent States via Language-Model Paradigms

Lorraine Yuan ⋅ Yu Nu

Adaptive Ad Load Design for Sponsored Search Markets

Mohammad Rashid ⋅ Hema Yoganarasimhan

A Splitting Method for SDE Terminal-Law Estimation

Rushil Gupta ⋅ Sandeep Juneja

Beyond Independent Generation: Set-Level Optimization for Generative Models

Yuqing Wu ⋅ Zishun Yu ⋅ Xinhua Zhang

Recovering Predictions without Regretting Decisions: Cone-constrained Prediction Recovery for Decision-Focused Learning

Junhyeong Lee ⋅ Sangjin Jin ⋅ Yongjae Lee

Democratizing Large-Scale Re-Optimization with LLM-Guided Model Patches

Tinghan Ye ⋅ Arnaud Deza ⋅ Ved Mohan ⋅ El Mehdi Er Raqabi ⋅ Pascal Van Hentenryck

PRICE: Adaptive LLM Test-time Compute under a Token Budget and Its Closed-form Pareto Frontier

Zhenyu Wang ⋅ zhu ⋅ Yifan Hu

BayesEvolve: Uncertainty-Aware Sequential Decision-Making with LLMs

Xuening Wu ⋅ Lei li ⋅ Shanyu ⋅ ZIQI SHI ⋅ Xinyan Yu ⋅ Qianya Xu ⋅ Yin Shenqin

Stopping Self-Excitement

Andrew Daw

Contextual Distributionally Robust Optimization with Causal and Continuous Structure: An Interpretable and Tractable Approach

Fenglin Zhang ⋅ Jie Wang

Hindsight Is 20/20: Making Regret Meaningful in Decision-Focused Learning

Vishal Gupta ⋅ Shammas Ahmed

Generative Exploration via Stochastic Inference in Monte Carlo Tree Search for Automatic Heuristic Design

Vu G Nam ⋅ Nguyen V Anh ⋅ Pham V Dat ⋅ Long Doan ⋅ Huynh Thi Thanh Binh

Improving Mixup Calibration with Wasserstein Distributionally Robust Optimization

Jiaming Hu ⋅ Yeping Jin ⋅ Debarghya Mukherjee ⋅ Yannis Paschalidis

Decision-Aware Information Acquisition for Optimization under Uncertainty

Chong Xiao Wang ⋅ Yan Bin Ng ⋅ Tanya Veeravalli ⋅ Tze-Yang Poon ⋅ Atsushi Nitanda ⋅ Jiao Liu ⋅ Yew Soon Ong

CoreFlow: Low-Rank Matrix Generative Models

Dongze Wu ⋅ Linglingzhi Zhu ⋅ Yao Xie

Optimizing Noise Schedules in Diffusion Models

Billy Jin ⋅ Harsha Honnappa ⋅ Baris Ata

Beyond Prediction Residuals: Conformal Regret Calibration for Robust Contextual Linear Optimization

Lingjie Zhao ⋅ Hansheng Jiang ⋅ Wei Qi

Uncertainty-Aware Budget Allocation for Online User Acquisition via Behavioral Mixture Likelihoods

Jayshmi A ⋅ Soumyajyoti Banerjee ⋅ Sunil Rathee

Best Arm Identification in Linear Bandits with Partially Observable Features

Sangjin Kim ⋅ Wonyoung Kim

Cross-Task Transfer in LLM Population Simulators: Identification and Failure Modes

Darcy Wang ⋅ Ziyuan Zhang ⋅ Ningyuan Chen ⋅ Vahid Sarhangian

Adaptive Top-$n$ Retained-Set Exploitation in Weakly Separated Bandit Regimes

Advaith Anand ⋅ Abhishek Umrawal

Does U-W Ratio Alignment Benefit Muon in LLM Pretraining?

Xuhe Zhang ⋅ X.Y. Han

Landscape of Policy Optimization: Infinite-Horizon Discounted MDPs with General State and Action

Xin Chen ⋅ Minda Zhao

Representation-Space Transition Kernels for Markov Chain Choice Models at Catalog Scale

Manuel Moran-Pelaez ⋅ Salvador K. Dzimah ⋅ Georgia Perakis

Beyond Prediction: Conformal Inference for Latent Distributional Parameters

Minxing Zheng ⋅ Wenbin Zhou ⋅ Shixiang Zhu

Variational Generative Thompson Sampling for Nonstationary Contextual Bandits

HWAN KYU SUNG ⋅ Seungki Min ⋅ Se-Young Yun

Optimal Feature Acquisition for Transformers

Andrew Li ⋅ Zhaoyu Xu

Cost-Aware Multi-LLM Aggregation under Hierarchical Pitman–Yor Dependence

Jingkai Huang ⋅ Will Ma ⋅ Zhengyuan Zhou

Bridging Learned Visual Perception and Symbolic Belief-Space Planning via Probabilistic Grounding

Guy Azran ⋅ Michael Navat ⋅ Sarah Keren

Online Pandora’s Box for Contextual LLM Cascading

Alexandre Belloni ⋅ Yan Chen ⋅ Yehua Wei

Online Diffusion Fine-tuning under Doob's $h$-transform Guidance

Zhengyi Guo ⋅ Jiayuan Sheng ⋅ David Yao ⋅ Wenpin Tang

Distributionally Robust Decision Focused Learning with Conformally Calibrated Ambiguity Sets

Xuhui Zhang ⋅ Hoomaan Maskan ⋅ Alp Yurtsever ⋅ Suvrit Sra

The Newsvendor with Distributional Advice

Liyao Chang

Future-Informed Actor-Critic

Samy Mokeddem ⋅ Gaspard Lambrechts ⋅ Adrien Bolland ⋅ Damien Ernst

Inference for Adapted Wasserstein Profiles under Policy Reoptimization

Viet Vu ⋅ Jose Blanchet ⋅ Johannes Wiesel ⋅ Ruiyu Han

Achieving $\epsilon^{-2}$ Sample Complexity for Single-Loop Actor-Critic under Minimal Assumptions

Ishaq Hamza ⋅ Zaiwei Chen

Scenario Augmentation for Rare Financial Events via Multimodal Latent Diffusion

Mahdi Arab Loodaricheh ⋅ Anita Raja ⋅ Indranil SenGupta

LLMs Can Design Near-Optimal OR Algorithms

Jackie Baek

Adversarial Training for Deep Hedging in Nonstationary Markets

Philipp Schneider ⋅ Lukas Looser ⋅ Antoine Garin ⋅ Shuhan Liu ⋅ Daniel Kuhn

The Price of Looking Ahead: Decision-Focused Learning for Multistage Decision-Making

Shuyi Chen ⋅ Shuai Wang ⋅ Shixiang Zhu

Generative Artificial Intelligence-Assisted Discovery of a New Euclidean Held-Karp Bound

Jinbiao Chen ⋅ Hanzhang Qin

Scaling Dual Conic Proxies for AC Optimal Power Flow

Guancheng Qiu ⋅ Pascal Van Hentenryck

Generation, Not Selection: LLM Proposals for Certified Access-Control Policy Mining

Gautam Kumar ⋅ Ravi Sundaram ⋅ Shamik Sural

Rectification Difficulty and Optimal Sample Allocation in LLM-Augmented Surveys

Zikun Ye ⋅ Hema Yoganarasimhan

Smart Fine-Tune, Then Rectify

Zikun Ye ⋅ Jinglong Zhao ⋅ Lei Wang

An Empirically Sharper Estimator for Confounding-Robust Reinforcement Learning

Kei Ishikawa

Design Experiments to Compare Multi-armed Bandit Algorithms

Huiling Meng ⋅ Ningyuan Chen ⋅ Xuefeng GAO

Preference-Uncertainty Aware Planning With Coverage Guarantees

William Zhang ⋅ Pavithra Harsha ⋅ Aurelie Lozano ⋅ Naoki Abe

Composition-Matched Randomization Inference for Auditing Generative-AI Decision Policies

Mingyang Chen ⋅ Yida Xu ⋅ Huiwen Chen ⋅ Yiming Lu ⋅ Wei Jin

Conformal-DRO: Distributionally Robust Optimization with Conformalized Ambiguity Set

Luhao Zhang ⋅ Shixiang Zhu

AnchorOpt: Structured Runtime-Control Optimization for Tool-Using Agents

Ruofeng Liu ⋅ Tenzin Gyaltsen ⋅ Wei Sun

The Curvature of Regret in Contextual Linear Optimization

Konstantinos Ziliaskopoulos ⋅ Alexander Vinel ⋅ Alice E Smith

Conformal Robustness in Prediction-Driven Decision-Making

Lingjie Zhao ⋅ Hansheng Jiang ⋅ Wei Qi

OutageDiT: A Generative Foundation Model for Power Outage Forecasting and Scenario Simulation

Yunqin Zhu ⋅ Feng Qiu ⋅ Yao Xie

Generative Decision-Focused Learning for Multistage Stochastic Convex Programming

Mahya Hemmati ⋅ Maryam Daryalal